A random number generator includes a counting value generator, an address generator, a static entropy source and a processing circuit. The counting value generator generates a first random number. The address generator generates an address signal. The static entropy source is connected with the address generator to receive the address signal and generates a second random number. The processing circuit is connected with the static entropy source and the counting value generator to receive the first random number and the second random number. After the first random number and the second random number are processed by the processing circuit, the processing circuit generates an output random number.
Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A random number generator, comprising: a counting value generator for generating a first random number; an address generator for generating an address signal; a static entropy source connected with the address generator to receive the address signal and generate a second random number; and a processing circuit connected with the static entropy source and the counting value generator to receive the first random number and the second random number, wherein after the first random number and the second random number are processed by the processing circuit, the processing circuit generates an output random number.
Electronic device security. A system for generating random numbers. Traditional random number generators can suffer from predictability or require complex physical processes. This invention provides a method to generate random numbers using a combination of generated values and a static entropy source. The system includes a counting value generator that produces an initial random number. An address generator creates an address signal. A static entropy source is coupled to the address generator, receiving the address signal to produce a second random number. A processing circuit is connected to both the static entropy source and the counting value generator. This circuit receives the first and second random numbers. After processing these two numbers, the processing circuit generates a final output random number. This approach leverages a static entropy source, potentially a readily available physical phenomenon or component, and combines its output with a computationally generated value to enhance the randomness of the final output.
2. The random number generator as claimed in claim 1 , wherein the static entropy source comprises a PUF cell array, and the PUF cell array comprises plural PUF memory cells, wherein after an enrollment on the plural PUF memory cells is completed, the PUF cell array stores plural random bits.
A random number generator system leverages a physical unclonable function (PUF) cell array as a static entropy source to produce cryptographic-quality random numbers. The PUF cell array consists of multiple PUF memory cells, each exhibiting unique and unpredictable variations due to inherent manufacturing process fluctuations. During an enrollment phase, these cells are programmed or measured to capture their intrinsic randomness, resulting in a set of stored random bits. The stored bits serve as a reliable entropy source for generating random numbers, ensuring high entropy and resistance to replication or prediction. This approach eliminates the need for external entropy sources, reducing system complexity while maintaining security. The PUF-based design provides a tamper-resistant mechanism for random number generation, suitable for applications requiring robust cryptographic operations. The system may integrate with other components to enhance randomness extraction or post-processing, ensuring compliance with cryptographic standards. The PUF cell array's inherent unpredictability ensures that the generated random numbers remain secure against attacks, even in adversarial environments.
3. The random number generator as claimed in claim 2 , wherein the counting value generator is a first linear feedback shift register, and the address generator is a second linear feedback shift register, wherein the first linear feedback shift register receives a first seed signal, and the second linear feedback shift register receives a second seed signal.
A random number generator system addresses the need for secure and unpredictable random number generation, particularly in cryptographic applications where predictability can compromise security. The system includes a counting value generator and an address generator, both implemented as linear feedback shift registers (LFSRs). The counting value generator, a first LFSR, receives a first seed signal to initialize its operation, while the address generator, a second LFSR, receives a second seed signal. The first LFSR produces a counting value that is used to index into a memory array, and the second LFSR generates an address within the memory array. The memory array stores a sequence of values, and the combination of the counting value and address determines the output random number. By using two separate LFSRs with distinct seed signals, the system enhances randomness and reduces predictability, improving security. The LFSRs are configured with feedback polynomials that ensure a long period before repeating sequences, further strengthening the randomness of the output. This design is particularly useful in applications requiring high-quality random numbers, such as encryption, key generation, and secure communication protocols.
4. The random number generator as claimed in claim 3 , wherein the random number generator further comprises a control circuit and a first dynamic entropy source, and the first dynamic entropy source is connected with the control circuit, wherein when a triggering signal is activated by the first dynamic entropy source, the control circuit selectively generates a first reseed signal to the first linear feedback shift register.
A random number generator system includes a linear feedback shift register (LFSR) that produces pseudo-random numbers based on a seed value. The system further includes a control circuit and a dynamic entropy source connected to the control circuit. The dynamic entropy source monitors environmental or system conditions to detect unpredictable events, such as hardware noise or external disturbances. When such an event occurs, the entropy source generates a triggering signal. Upon receiving this signal, the control circuit evaluates the event's suitability as a source of entropy. If the event meets predefined criteria, the control circuit generates a reseed signal to the LFSR, causing it to update its seed value using the new entropy. This reseed operation enhances the randomness of the generated numbers by incorporating external, unpredictable inputs. The system ensures that the LFSR is periodically refreshed with high-quality entropy, improving the cryptographic security of the random numbers produced. The dynamic entropy source may include sensors or hardware components that capture real-world variability, while the control circuit implements logic to validate and process the entropy before reseed operations. This approach mitigates vulnerabilities in pseudo-random number generation by combining deterministic and non-deterministic elements.
5. The random number generator as claimed in claim 4 , wherein the control circuit receives the address signal and the first random number and combines a first portion of the address signal and a first portion of the first random number as the first reseed signal, wherein when the triggering signal is activated by the first dynamic entropy source, the control circuit transmits the first reseed signal to the first linear feedback shift register.
This invention relates to a random number generator (RNG) system that enhances security by dynamically reseeding a linear feedback shift register (LFSR) using entropy from an external source. The system addresses the vulnerability of traditional LFSRs, which can be predictable if their initial seed is compromised or if the feedback polynomial is known. The invention improves unpredictability by incorporating dynamic entropy sources, such as environmental noise or user input, to periodically reseed the LFSR. The RNG includes a control circuit that processes an address signal and a first random number generated by the LFSR. The control circuit extracts a first portion of the address signal and a first portion of the first random number, then combines them to form a first reseed signal. When a triggering signal from a dynamic entropy source is activated, the control circuit sends this reseed signal to the LFSR, updating its state. This dynamic reseeding mechanism ensures that the LFSR's output remains unpredictable, even if an attacker attempts to reverse-engineer its operation. The system may include multiple LFSRs and entropy sources, with the control circuit managing reseeding operations across them to further enhance security. The invention is particularly useful in cryptographic applications where high entropy and resistance to prediction are critical.
6. The random number generator as claimed in claim 4 , wherein the control circuit receives the address signal and the first random number and combines a first portion of the address signal and a first portion of the first random number as the first reseed signal, wherein after the control circuit performs a logical operation on the triggering signal and a second portion of the first random number, the control circuit selectively transmits the first reseed signal to the first linear feedback shift register.
This invention relates to a random number generator system, specifically an improved method for reseeding a linear feedback shift register (LFSR) to enhance randomness and security. The problem addressed is the predictability of random number sequences in conventional LFSR-based generators, which can be exploited in cryptographic applications. The system includes a control circuit that receives an address signal and a first random number generated by a first LFSR. The control circuit processes these inputs to produce a reseed signal. A first portion of the address signal is combined with a first portion of the first random number to form the reseed signal. Additionally, the control circuit performs a logical operation on a triggering signal and a second portion of the first random number to determine whether to transmit the reseed signal to the first LFSR. This selective reseeding mechanism improves the unpredictability of the output sequence by incorporating external inputs (address signals) and conditional logic, making it harder to reverse-engineer the random number generation process. The system may also include a second LFSR and a second control circuit for further enhancing randomness through parallel or cascaded operations. The overall design aims to strengthen cryptographic security by reducing patterns in generated random numbers.
7. The random number generator as claimed in claim 4 , wherein when the triggering signal is activated by the first dynamic entropy source, the control circuit selectively generates a second reseed signal to the second linear feedback shift register.
A random number generator system leverages multiple dynamic entropy sources to enhance cryptographic security. The system includes at least two linear feedback shift registers (LFSRs) that generate pseudorandom outputs. A control circuit monitors entropy sources, such as environmental noise or user input, to detect significant entropy events. When a first entropy source triggers a signal, the control circuit selectively activates a reseed operation for a second LFSR. This reseed operation updates the LFSR's state using entropy from the first source, improving randomness. The system ensures continuous entropy injection, reducing predictability in cryptographic applications. The control circuit may also manage synchronization between LFSRs to maintain output quality. This design addresses vulnerabilities in traditional LFSR-based generators by dynamically integrating multiple entropy inputs, enhancing resistance to statistical attacks. The reseed mechanism ensures that even if one LFSR is compromised, the second LFSR remains secure due to independent entropy sources. The system is particularly useful in secure communications, authentication, and key generation where high-quality randomness is critical.
8. The random number generator as claimed in claim 4 , wherein the first dynamic entropy source comprises: a first ring oscillator comprising n stages of delay units in ring connection, and generating a first oscillation signal; a second ring oscillator comprising m stages of delay units in ring connection, and generating a second oscillation signal, wherein n and m are odd numbers and m is not equal to n; an XOR gate receiving the first oscillation signal and the second oscillation signal, and generating an output signal; and a latch receiving the output signal, wherein the output signal is latched by the latch according to a first clock signal, so that the triggering signal is generated.
A random number generator system leverages dynamic entropy sources to produce unpredictable outputs. The system addresses the challenge of generating high-quality random numbers by utilizing multiple ring oscillators with different configurations to introduce inherent variability. The first dynamic entropy source includes two ring oscillators: a first ring oscillator with n stages of delay units and a second ring oscillator with m stages of delay units, where n and m are odd numbers and m is not equal to n. These oscillators generate distinct oscillation signals due to their differing stage counts. The oscillation signals are combined using an XOR gate, producing an output signal that reflects the phase differences between the two oscillators. This output signal is then latched by a latch circuit synchronized to a first clock signal, generating a triggering signal. The differing oscillator configurations ensure that the output is highly unpredictable, as the phase relationships between the oscillators are sensitive to environmental and manufacturing variations. This approach enhances the entropy of the random number generator, making it suitable for cryptographic and security applications where high-quality randomness is critical.
9. The random number generator as claimed in claim 3 , wherein the random number generator further comprises a second dynamic entropy source, and the second dynamic entropy source provides the first seed signal and the second seed signal to the first linear feedback shift register and the second linear feedback shift register, respectively.
A random number generator system enhances cryptographic security by incorporating multiple dynamic entropy sources to improve randomness. The system includes at least two linear feedback shift registers (LFSRs) that generate pseudorandom sequences based on seed signals. Each LFSR operates independently, with one LFSR producing a first pseudorandom sequence and another producing a second pseudorandom sequence. These sequences are combined to generate a final random output, increasing unpredictability. The system further includes a second dynamic entropy source that provides seed signals to both LFSRs, ensuring that the initial states of the LFSRs are derived from high-entropy inputs. This dual-source approach reduces the risk of predictability in the pseudorandom sequences, making the generator more resistant to cryptographic attacks. The dynamic entropy sources may include hardware-based randomness generators, environmental noise, or other unpredictable physical phenomena. By leveraging multiple entropy sources and LFSRs, the system achieves a higher level of randomness, suitable for cryptographic applications where security is critical.
10. The random number generator as claimed in claim 9 , wherein the second dynamic entropy source is a meta-stability circuit, and the meta-stability circuit comprises: x meta-stability devices, wherein each of the x meta-stability devices generates one-bit random signal, wherein when a start signal is activated, the x meta-stability devices generate the first seed signal with x bits; and y meta-stability devices, wherein each of the y meta-stability devices generates one-bit random signal, wherein when the start signal is activated, the y meta-stability devices generate the second seed signal with y bits, wherein x and y are positive integers.
A random number generator system leverages meta-stability circuits as a dynamic entropy source to produce cryptographically secure random numbers. The system addresses the need for high-quality randomness in applications requiring strong security, such as cryptographic key generation, by utilizing inherent physical uncertainties in electronic circuits. The meta-stability circuit comprises two sets of meta-stability devices: a first set of x devices generating an x-bit first seed signal and a second set of y devices generating a y-bit second seed signal, where x and y are positive integers. When a start signal is activated, both sets of devices produce their respective seed signals simultaneously, ensuring rapid and parallel entropy collection. The meta-stability devices exploit the unpredictable behavior of electronic components near their switching thresholds to generate random bits, enhancing resistance to deterministic attacks. This design improves upon traditional entropy sources by providing a scalable, hardware-based solution with high throughput and reliability. The system is particularly suited for environments where deterministic algorithms or software-based random number generators are insufficient.
11. The random number generator as claimed in claim 10 , wherein a first meta-stability device of the x meta-stability devices comprises: a first switching device, wherein a first terminal of the first switching device receives a first voltage, and a control terminal of the first switching device receives the start signal; a second switching device, wherein a first terminal of the second switching device receives the first voltage, and a control terminal of the second switching device receives the start signal; a first inverter operated between a supply voltage and a ground voltage, wherein an input terminal of the first inverter is connected with a second terminal of the first switching device, and an output terminal of the first inverter is connected with a second terminal of the second switching device; and a second inverter operated between the supply voltage and the ground voltage, wherein an input terminal of the second inverter is connected with the second terminal of the second switching device, and an output terminal of the second inverter is connected with the second terminal of the first switching device, wherein the first voltage is equal to a half of the supply voltage, wherein when the start signal is not activated, the first switching device and the second switching device are in a close state, wherein when the start signal is activated, the first switching device and the second switching device are in an open state.
A random number generator system includes multiple meta-stability devices to produce random outputs. Each meta-stability device contains two switching devices, two inverters, and a voltage control mechanism. The first switching device has a first terminal connected to a voltage source set at half the supply voltage and a control terminal receiving a start signal. The second switching device is similarly configured. The first inverter connects between the second terminal of the first switching device and the second terminal of the second switching device, while the second inverter connects in reverse. When the start signal is inactive, both switching devices remain closed, maintaining a stable state. Upon activation of the start signal, the switching devices open, allowing the inverters to enter a meta-stable state, producing random output signals. This design leverages meta-stability to generate unpredictable digital outputs, addressing the need for secure and reliable random number generation in electronic systems. The system ensures high entropy by exploiting transient meta-stable conditions triggered by the start signal.
12. A random number generator, comprising: a first dynamic entropy source for generating a triggering signal; a second dynamic entropy source for generating a first seed signal and a second seed signal; a counting value generator connected with the second dynamic entropy source to receive the first seed signal and generate a first random number; an address generator connected with the second dynamic entropy source to receive the second seed signal and generate an address signal; a static entropy source connected with the address generator to receive the address signal and generate a second random number; a processing circuit connected with the static entropy source and the counting value generator to receive the first random number and the second random number, wherein after the first random number and the second random number are processed by the processing circuit, the processing circuit generates an output random number; and a control circuit connected with the first dynamic entropy source to receive the triggering signal, wherein when the triggering signal is activated, the control circuit selectively generates a first reseed signal to the counting value generator.
This invention relates to a random number generator designed to enhance cryptographic security by combining dynamic and static entropy sources. The system addresses the challenge of generating unpredictable random numbers for cryptographic applications, where weak randomness can lead to security vulnerabilities. The generator includes two dynamic entropy sources: one produces a triggering signal to initiate operations, while the other generates two seed signals. A counting value generator uses the first seed signal to produce a first random number, while an address generator uses the second seed signal to create an address signal. A static entropy source, accessed via the address signal, generates a second random number. These two random numbers are processed by a circuit to produce a final output random number. A control circuit monitors the triggering signal and, when activated, sends a reseed signal to the counting value generator to refresh its output. This design ensures high entropy by combining dynamic and static sources, improving resistance to prediction attacks. The system is particularly useful in cryptographic applications requiring robust randomness.
13. The random number generator as claimed in claim 12 , wherein the static entropy source comprises a PUF cell array, and the PUF cell array comprises plural PUF memory cells, wherein after an enrollment on the plural PUF memory cells is completed, the PUF cell array stores plural random bits.
14. The random number generator as claimed in claim 13 , wherein the counting value generator is a first linear feedback shift register, and the address generator is a second linear feedback shift register, wherein the first linear feedback shift register receives a first seed signal, and the second linear feedback shift register receives a second seed signal.
A random number generator system includes a counting value generator and an address generator to produce random numbers. The counting value generator and address generator are implemented as linear feedback shift registers (LFSRs). The first LFSR generates a counting value based on a first seed signal, while the second LFSR generates an address based on a second seed signal. The system combines these outputs to produce a random number. LFSRs are used for their ability to generate pseudorandom sequences with good statistical properties. The use of separate LFSRs for counting and addressing improves randomness by reducing correlation between the generated values. This design is useful in applications requiring high-quality random numbers, such as cryptography, simulations, or gaming, where predictability must be minimized. The system ensures that the random number generation process is deterministic yet unpredictable without knowledge of the seed values. The separation of counting and addressing functions enhances security and reduces bias in the output.
15. The random number generator as claimed in claim 14 , wherein the control circuit receives the address signal and the first random number and combines a first portion of the address signal and a first portion of the first random number as the first reseed signal, wherein when the triggering signal is activated by the first dynamic entropy source, the control circuit transmits the first reseed signal to the first linear feedback shift register.
This invention relates to a random number generator (RNG) system that enhances entropy by combining signals from dynamic entropy sources with linear feedback shift registers (LFSRs). The system addresses the challenge of generating high-quality random numbers by improving the unpredictability of LFSRs, which are deterministic and can be vulnerable to attacks if not properly seeded. The RNG includes a control circuit that processes signals from at least one dynamic entropy source, such as a physical unclonable function (PUF) or a noise-based source. The control circuit receives an address signal and a first random number, then combines a portion of the address signal with a portion of the first random number to generate a reseed signal. When the dynamic entropy source triggers an activation signal, the control circuit sends this reseed signal to an LFSR, effectively reseeding it to improve randomness. This mechanism ensures that the LFSR's output remains unpredictable by periodically introducing entropy from the dynamic source. The system may include multiple LFSRs, each reseeding independently based on different portions of the address signal and random number. The control circuit dynamically adjusts the reseeding process to maintain high entropy levels, making the RNG suitable for cryptographic applications where security is critical. The invention improves upon traditional LFSR-based RNGs by integrating real-time entropy sources, reducing predictability and enhancing resistance to cryptographic attacks.
16. The random number generator as claimed in claim 14 , wherein the control circuit receives the address signal and the first random number and combines a first portion of the address signal and a first portion of the first random number as the first reseed signal, wherein after the control circuit performs a logical operation on the triggering signal and a second portion of the first random number, the control circuit selectively transmits the first reseed signal to the first linear feedback shift register.
A random number generator system includes a control circuit and at least one linear feedback shift register (LFSR) for generating random numbers. The system addresses the need for improved randomness and security in cryptographic applications by dynamically reseeding the LFSR to enhance unpredictability. The control circuit receives an address signal and a first random number generated by the LFSR. The control circuit processes these inputs by combining a first portion of the address signal with a first portion of the first random number to produce a first reseed signal. Additionally, the control circuit performs a logical operation on a triggering signal and a second portion of the first random number to determine whether to transmit the first reseed signal to the LFSR. This selective reseeding mechanism ensures that the LFSR is periodically updated with new seed values derived from both the address signal and the previously generated random number, improving the system's resistance to prediction and attacks. The system may include multiple LFSRs, each receiving distinct reseed signals to further enhance randomness. The control circuit's logic ensures that reseeding occurs only under specific conditions, balancing performance and security. This approach is particularly useful in applications requiring high-quality random numbers, such as cryptographic key generation and secure communication protocols.
17. The random number generator as claimed in claim 12 , wherein the first dynamic entropy source comprises: a first ring oscillator comprising n stages of delay units in ring connection, and generating a first oscillation signal; a second ring oscillator comprising m stages of delay units in ring connection, and generating a second oscillation signal, wherein n and m are odd numbers and m is not equal to n; an XOR gate receiving the first oscillation signal and the second oscillation signal, and generating an output signal; and a latch receiving the output signal, wherein the output signal is latched by the latch according to a first clock signal, so that the triggering signal is generated.
A random number generator system leverages dynamic entropy sources to produce unpredictable outputs. The system addresses the challenge of generating high-quality random numbers by utilizing multiple ring oscillators with different configurations to introduce inherent variability. The first dynamic entropy source includes two ring oscillators: a first ring oscillator with n stages of delay units and a second ring oscillator with m stages of delay units, where n and m are odd numbers and m is not equal to n. These oscillators generate distinct oscillation signals due to their differing stage counts. The signals are combined using an XOR gate, producing an output signal that reflects the phase differences between the oscillators. This output is then latched by a latch circuit, which synchronizes the signal to a first clock signal, generating a triggering signal. The differing oscillator configurations ensure that the output is highly unpredictable, enhancing the entropy of the random number generator. This approach mitigates vulnerabilities in traditional random number generation methods by leveraging physical variations in oscillator behavior.
18. The random number generator as claimed in claim 12 , wherein the second dynamic entropy source is a meta-stability circuit, and the meta-stability circuit comprises: x meta-stability devices, wherein each of the x meta-stability devices generates one-bit random signal, wherein when a start signal is activated, the x meta-stability devices generate the first seed signal with x bits; and y meta-stability devices, wherein each of the y meta-stability devices generates one-bit random signal, wherein when the start signal is activated, the y meta-stability devices generate the second seed signal with y bits, wherein x and y are positive integers.
A random number generator system leverages meta-stability circuits as a dynamic entropy source to produce cryptographically secure random numbers. The system addresses the need for high-quality randomness in applications like cryptography, where predictable or biased outputs can compromise security. The meta-stability circuit consists of two sets of meta-stability devices: one set generates a first seed signal with x bits, and another set generates a second seed signal with y bits, where x and y are positive integers. When a start signal is activated, each meta-stability device in the respective sets independently produces a one-bit random signal, contributing to the overall seed signals. The meta-stability devices exploit inherent physical uncertainties in electronic circuits to generate unpredictable outputs, enhancing entropy. This design ensures that the random number generator can produce high-entropy seeds for cryptographic operations, mitigating risks associated with deterministic or low-entropy sources. The system is particularly useful in secure communication, encryption, and key generation, where reliability and unpredictability are critical.
19. The random number generator as claimed in claim 18 , wherein a first meta-stability device of the x meta-stability devices comprises: a first switching device, wherein a first terminal of the first switching device receives a first voltage, and a control terminal of the first switching device receives the start signal; a second switching device, wherein a first terminal of the second switching device receives the first voltage, and a control terminal of the second switching device receives the start signal; a first inverter operated between a supply voltage and a ground voltage, wherein an input terminal of the first inverter is connected with a second terminal of the first switching device, and an output terminal of the first inverter is connected with a second terminal of the second switching device; and a second inverter operated between the supply voltage and the ground voltage, wherein an input terminal of the second inverter is connected with the second terminal of the second switching device, and an output terminal of the second inverter is connected with the second terminal of the first switching device, wherein the first voltage is equal to a half of the supply voltage, wherein when the start signal is not activated, the first switching device and the second switching device are in a close state, wherein when the start signal is activated, the first switching device and the second switching device are in an open state.
This invention relates to a random number generator utilizing meta-stability devices to produce random outputs. The generator addresses the need for reliable and efficient random number generation in digital systems, particularly where deterministic behavior is undesirable. The system employs multiple meta-stability devices, each configured to introduce controlled instability in response to a start signal, thereby generating random bit sequences. A meta-stability device in this system includes two switching devices, each receiving a first voltage equal to half the supply voltage and controlled by the start signal. When the start signal is inactive, the switching devices remain closed, maintaining a stable state. Upon activation of the start signal, the switching devices open, allowing the device to enter a meta-stable state. The device further includes two inverters connected in a cross-coupled configuration, with their inputs and outputs linked to the switching devices. This arrangement creates a feedback loop that amplifies small voltage fluctuations, leading to random output transitions. The interplay between the switching devices and inverters ensures that the system produces unpredictable binary outputs when triggered. The design leverages inherent circuit noise and timing variations to achieve true randomness, making it suitable for cryptographic applications and other security-sensitive systems.
20. The random number generator as claimed in claim 12 , wherein the processing circuit comprises: a first XOR circuit, wherein a first input terminal of the first XOR circuit is connected with the static entropy source to receive the second random number, and a second input terminal of the first XOR circuit is connected with the counting value generator to receive the first random number; a first latch circuit, wherein a data input terminal of the first latch circuit is connected with an output terminal of the first XOR circuit, a clock input terminal of the first latch circuit receives a second clock signal from the control circuit, and a data output terminal of the first latch circuit generates a third random number; a second XOR circuit, wherein a first input terminal of the second XOR circuit is connected with the static entropy source to receive the second random number, and a second input terminal of the second XOR circuit is connected with the data output terminal of the first latch circuit to receive the third random number; and a second latch circuit, wherein a data input terminal of the second latch circuit is connected with an output terminal of the second XOR circuit, a clock input terminal of the second latch circuit receives a third clock signal from the control circuit, and a data output terminal of the second latch circuit generates the output random number.
A random number generator system enhances cryptographic security by combining static entropy sources with dynamic counting values. The system includes a processing circuit that improves randomness by sequentially applying XOR operations and latching mechanisms. The first XOR circuit combines a static entropy source output (second random number) with a counting value (first random number) to produce an intermediate result. This result is latched by a first latch circuit, synchronized by a second clock signal, generating a third random number. A second XOR circuit then combines the static entropy source output with the latched third random number, producing another intermediate result. This final result is latched by a second latch circuit, synchronized by a third clock signal, to generate the output random number. The system ensures high-quality randomness by leveraging multiple stages of XOR operations and controlled clock synchronization, reducing predictability and enhancing security for cryptographic applications. The static entropy source provides initial randomness, while the counting value generator introduces dynamic variability, and the sequential XOR and latch operations further refine the output. This design is particularly useful in secure communication systems where unpredictable random numbers are critical.
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February 7, 2020
April 5, 2022
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